The stellare Inhalt von weichen Röntgenhimmelsdurchmusterungen

• Antragsteller: Professor Dr. Jürgen H.M.M. Schmitt
• Fachliche Zuordnung: Astrophysik und Astronomie
• Förderung: Förderung von 2016 bis 2020
• Projektkennung: Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 314771936

• Erstellungsjahr: 2021

Zusammenfassung der Projektergebnisse

Within the context of the project "The stellar content of wide-angle soft X-ray sky surveys" a mathematically and statistically sound framework for the identification of coronal X-ray sources in X-ray all-sky surveys was developed. The major new ingredient is the availabilility of a complete census of objects as available through the Gaia catalog, which is expected to contain – at least eventually – all stellar counterparts of X-ray sources found in the ROSAT and eROSITA all-sky surveys. The chosen approach allows the consideration of additional source parameters (for example, chromospheric emissions), which would increase or decrease the probability of the association of a given X-ray source with a Gaia catalog entry, however, currently such features have not been implemented. Another important feature is the fact that the identification effort extends over the whole sky, i.e., in particular over low galactic latitudes which are normally ignored by identification efforts driven by extragalactic sources; at low galactic latitudes the stellar density can become extremely large, which obviously aggravates the source contamination problem. The new method has been applied both to the sources from the “old” ROSAT all-sky survey as well as the ongoing eROSITA all-sky survey.

Projektbezogene Publikationen (Auswahl)

• 2020.: Updated X-ray view of the Hyades cluster, in Astronomy and Astrophysics 640
  Freund, S., Robrade, J., Schneider, P. C., Schmitt, J. H. M. M.
  
• 2021. eROSITA X-ray scan of the eta Chamaeleontis cluster
  Robrade, J., Czesla, S., Freund, S., et al.
  
• 2021. The eROSITA Final Equatorial-Depth Survey (eFEDS). The stellar counterparts of eROSITA sources identified by machine learning and Bayesian algorithms
  Schneider, P. C., Freund, S., Czesla, S., et al.
  
• 2021. The eROSITA Final Equatorial-Depth Survey (eFEDS): Identification and characterization of the counterparts to the point-like sources
  Salvato, M., Wolf, J., Dwelly, T., et al.
  
• 2021. X-raying the Sco-Cen OB association: The low-mass stellar population revealed by eROSITA
  Schmitt, J. H. M. M., Czesla, S., Freund, S., et al.